Aegiq and Pixel Photonics partner on quantum computing
By combining Aegiq’s single-photon sources with Pixel Photonics’ waveguide-integrated single-photon detectors, the companies aim to break through the current quantum computing performance ceiling and unlock new possibilities for scalable, real-world quantum systems
Aegiq, a photonic quantum computing company, and Pixel Photonics, a single-photon detection company, have signed a memorandum of understanding to bring their technologies together on a shared photonic platform. The collaboration will combine Aegiq’s single-photon sources with Pixel Photonics’ waveguide-integrated superconducting nanowire detectors.
According to the companies, this marks an important step towards building a scalable and practical quantum computing stack, where high-performance photon detection is key to enabling real-world quantum applications.
Aegiq takes a modular approach to building a quantum computer, aiming to offer customers a path to rapid scale and commercial usage. The company says its technology reliably creates photons on demand at GHz clock speeds, routes these through its processors, and finally detects and measures them – all in telecom wavelengths.
Pixel Photonics’ single-photon detectors seek to combine seamless photonic platform integration with exceptional performance and scalability. The company says its unique waveguide integration approach offers the performance and scalability required for enabling advanced applications in quantum and beyond.
“This collaboration combines Aegiq's on-demand telecom photon sources with Pixel Photonics' unique detector technology,” said Scott Dufferwiel, CEO at Aegiq. “By bringing these technologies together, we are unlocking quantum computing at scale.”
Nicolai Walter, CEO at Pixel Photonics, added: “Pixel Photonics’ detectors are designed to seamlessly integrate with photonic platforms. Our high-performance waveguide-integrated devices are highly scalable and align perfectly with Aegiq plans to deliver reliable photonic quantum computing at scale.”
